检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

4,455 篇 会议
67 篇 期刊文献
18 册 图书
2 篇 学位论文

馆藏范围

4,542 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,617 篇 工学
- 1,755 篇 计算机科学与技术...
- 1,200 篇 信息与通信工程
- 968 篇 软件工程
- 733 篇 电气工程
- 310 篇 光学工程
- 156 篇 电子科学与技术（可...
- 129 篇 生物工程
- 101 篇 控制科学与工程
- 83 篇 生物医学工程（可授...
- 74 篇 仪器科学与技术
- 65 篇 机械工程
- 41 篇 网络空间安全
- 37 篇 化学工程与技术
- 27 篇 动力工程及工程热...
- 27 篇 安全科学与工程
- 18 篇 交通运输工程
- 17 篇 土木工程
1,099 篇 理学
- 826 篇 物理学
- 313 篇 数学
- 138 篇 生物学
- 74 篇 统计学（可授理学、...
- 37 篇 系统科学
- 36 篇 化学
1,077 篇 医学
- 1,059 篇 临床医学
- 43 篇 基础医学(可授医学...
- 35 篇 药学(可授医学、理...
181 篇 管理学
- 101 篇 图书情报与档案管...
- 90 篇 管理科学与工程(可...
- 25 篇 工商管理
37 篇 法学
- 34 篇 社会学
13 篇 军事学
10 篇 经济学
10 篇 文学
8 篇 教育学
6 篇 农学

主题

546 篇 image coding
422 篇 visual communica...
388 篇 image processing
338 篇 visualization
269 篇 feature extracti...
218 篇 image segmentati...
171 篇 image reconstruc...
169 篇 image compressio...
165 篇 video coding
144 篇 cameras
144 篇 training
142 篇 humans
118 篇 image color anal...
113 篇 image quality
112 篇 deep learning
109 篇 motion estimatio...
102 篇 image edge detec...
100 篇 decoding
99 篇 image enhancemen...
99 篇 image analysis

机构

36 篇 shanghai jiao to...
29 篇 institute of ima...
25 篇 school of electr...
23 篇 beijing universi...
20 篇 university of sc...
20 篇 shanghai jiao to...
16 篇 shanghai jiao to...
16 篇 tianjin univ sch...
14 篇 school of electr...
13 篇 peking univ inst...
12 篇 university of el...
11 篇 school of remote...
11 篇 cas key laborato...
11 篇 tsinghua univ de...
10 篇 univ sci & techn...
10 篇 zhejiang univers...
10 篇 xidian univ sch ...
10 篇 peking universit...
10 篇 beijing univ pos...
10 篇 institute of ima...

作者

36 篇 zhai guangtao
27 篇 sumei li
25 篇 song li
24 篇 guangtao zhai
22 篇 li sumei
19 篇 shan liu
18 篇 li li
18 篇 li song
18 篇 min xiongkuo
16 篇 dong liu
16 篇 yang xiaokang
15 篇 zhenzhong chen
15 篇 andré kaup
15 篇 ma siwei
15 篇 gao wen
14 篇 chen zhibo
13 篇 xie rong
13 篇 xiongkuo min
12 篇 xin jin
11 篇 heming sun

语言

4,458 篇 英文
59 篇 土耳其文
32 篇 中文
12 篇 其他

检索条件"任意字段=1997 Conference on Visual Communications and Image Processing"

共 4542 条记录，以下是131-140 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

A Lightweight Tire Tread image Classification Network

A Lightweight Tire Tread Image Classification Network

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Zhang, Fenglei Li, Da Li, Shenghua Guan, Weili Liu, Meng Shandong Jianzhu Univ Jinan Peoples R China Monash Univ Elbourne Australia

ISBN: (纸本)9781665475921

VCIP 2022 "Tire pattern image classification based on lightweight network challenge" aims to design lightweight networks that correctly classify tire surface tread patterns and indentation images using less overhead. To this end, we present a novel lightweight tire tread classification network. Concretely, we adopt the ShuffleNet-V2-x0.5 network as our backbone. To reduce the computation complexity, we introduce the Space-To-Depth and Anti-Alias Downsampling modules to pre-process the input image. Moreover, to enhance the classification ability of our model, we adopt the knowledge distillation strategy by considering Vision Transformer as the teacher network. To ensure the robustness of our model, we pre-train it on imageNet and fine-tune the training set of the challenge. Experiments on the challenge dataset demonstrate that our model achieves superior performance, with 99.00% classification accuracy, 25.51M FLOPs, and 0.20M parameters.

关键词： tire tread image classification knowledge distillation lightweight image classification

来源：评论

学校读者我要写书评

暂无评论

Autonomous visual Moderation System (AutoMod) 31

Autonomous Visual Moderation System (AutoMod)

引用

31st IEEE conference on Signal processing and communications Applications (SIU)

作者： Bahtiyar, Huseyin Katipoglu, Bahadir Irfan Yuksel, Eda Toroslu, Ismail Hakki Karagoz, Pinar VLMedia R&D Dept Gumus Blok K1-1 ODTU TEKNOKENT Ankara Turkiye Middle East Tech Univ METU Dept Comp Engn TR-06800 Ankara Turkiye

ISBN: (纸本)9798350343557

Automod, the content moderation system, is an artificial intelligence solution that enables the detection of similarities and inconsistencies in visual content (image, video, etc.). It is designed as a content moderation system to detect the similarity and inconsistencies of user-generated visual content (images and videos). With the similarity module installed, labor savings of 15% were achieved, and F1 score results of 90% and higher were achieved for nonconformity detection models. More than 100.000 images can be evaluated daily, and the system's load was tested. Similarly, keyframes obtained from at least 65.000 video content that can be evaluated daily were passed through nonconformity models, and load test was applied.

关键词： image processing Machine Learning Deep Learning

来源：评论

学校读者我要写书评

暂无评论

Large-Scale Crowdsourcing Subjective Quality Evaluation of Learning-Based image Coding

Large-Scale Crowdsourcing Subjective Quality Evaluation of L...

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Upenik, Evgeniy Testolina, Michela Ascenso, Joao Pereira, Fernando Ebrahimi, Touradj Ecole Polytech Fed Lausanne Multimedia Signal Proc Grp Lausanne Switzerland Inst Super Tecn Inst TelecomunicacOes Lisbon Portugal

ISBN: (纸本)9781728185514

Learning-based image codecs produce different compression artifacts, when compared to the blocking and blurring degradation introduced by conventional image codecs, such as JPEG, JPEG 2000 and HEIC. In this paper, a crowdsourcing based subjective quality evaluation procedure was used to benchmark a representative set of end-to-end deep learning-based image codecs submitted to the MMSP'2020 Grand Challenge on Learning-Based image Coding and the JPEG AI Call for Evidence. For the first time, a double stimulus methodology with a continuous quality scale was applied to evaluate this type of image codecs. The subjective experiment is one of the largest ever reported including more than 240 pair-comparisons evaluated by 118 naive subjects. The results of the benchmarking of learning-based image coding solutions against conventional codecs are organized in a dataset of differential mean opinion scores along with the stimuli and made publicly available.

关键词： deep learning image coding learning-based compression subjective evaluation visual quality crowdsourcing

来源：评论

学校读者我要写书评

暂无评论

MAiVAR: Multimodal Audio-image and Video Action Recognizer

MAiVAR: Multimodal Audio-Image and Video Action Recognizer

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Shaikh, Muhammad Bilal Chai, Douglas Islam, Syed Mohammed Shamsul Akhtar, Naveed Edith Cowan Univ 270 Joondalup Dr Perth WA 6027 Australia Univ Western Australia 35 Stirling Highway Perth WA 6009 Australia

ISBN: (纸本)9781665475921

Currently, action recognition is predominately performed on video data as processed by CNNs. We investigate if the representation process of CNNs can also be leveraged for multimodal action recognition by incorporating image-based audio representations of actions in a task. To this end, we propose Multimodal Audio-image and Video Action Recognizer (MAiVAR), a CNN-based audio-image to video fusion model that accounts for video and audio modalities to achieve superior action recognition performance. MAiVAR extracts meaningful image representations of audio and fuses it with video representation to achieve better performance as compared to both modalities individually on a large-scale action recognition dataset.

关键词： Large dataset

来源：评论

学校读者我要写书评

暂无评论

Optimized MobileNetV2 Based on Model Pruning for image Classification

Optimized MobileNetV2 Based on Model Pruning for Image Class...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Xiao, Peng Pang, Yuliang Feng, Hao Hao, Yu Xian Univ Posts & Telecommunicat Ctr Image & Informat Proc (CIIP) Xian Peoples R China

ISBN: (纸本)9781665475921

Due to the large memory requirement and a large amount of computation, traditional deep learning networks cannot run on mobile devices as well as embedded devices. In this paper, we propose a new mobile architecture combining MobileNetV2 and pruning, which further decreases the Flops and number of parameters. The performance of MobileNetV2 has been widely demonstrated, and pruning operation can not only allow further model compression but also prevent overfitting. We have done ablation experiments at CIIP Tire Data for different pruning combinations. In addition, we introduced a global hyperparameter to effectively weigh the accuracy and precision. Experiments show that the accuracy of 98.3 % is maintained under the premise that the model size is only 804.5 KB, showing better performance than the baseline method.

关键词： model compression MobileNetV2 pruning

来源：评论

学校读者我要写书评

暂无评论

KonIQ-10k-LT: Overcoming Score Priors in Blind image Quality Assessment Under Imbalanced Distributions

KonIQ-10k-LT: Overcoming Score Priors in Blind Image Quality...

引用

2024 conference on visual communications and image processing

作者： Yuan, Desen Wang, Lei Univ Elect Sci & Technol China Chengdu Peoples R China

ISBN: (纸本)9798331529543;9798331529550

Blind image Quality Assessment (BIQA) is essential in computational vision for predicting the visual quality of digital images without reference counterparts. Despite advancements through convolutional neural networks (CNNs), a significant challenge in BIQA remains the long-tail distribution of image quality scores, leading to biased training and reduced model generalization. To address this, we restructured the KonIQ-10k dataset to create an imbalanced version named KonIQ-10k-LT, manipulating the distribution of image quality scores to have opposing distributions in the training and validation sets. This restructuring increases the proportion of certain quality scores in the training set while decreasing them in the validation set. Experimental results show a significant performance decline of BIQA models on the KonIQ-10k-LT dataset compared to the original KonIQ-10k, highlighting the challenge posed by the long-tail distribution. To mitigate this issue, we propose a Proportion Weighted Balancing (PWB) method as a baseline, designed to enhance the robustness and generalization ability of BIQA models. Our findings demonstrate that the proposed WB method improves the performance and reliability of BIQA models under these challenging conditions.

关键词： Blind image quality assessment Long-tail learning

来源：评论

学校读者我要写书评

暂无评论

Video Coding Pre-processing Based on Rate-Distortion Optimized Weighted Guided Filter

Video Coding Pre-Processing Based on Rate-Distortion Optimiz...

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Huang, Xi Jia, Luheng Wang, Han Jia, Kebin Beijing Univ Technol Fac Informat Technol Beijing Peoples R China

ISBN: (纸本)9781728185514

In video coding, it is always an intractable problem to compress high frequency components including noise and visually imperceptible content that consumes large amount bandwidth resources while providing limited quality improvement. Direct using of denoising methods causes coding performance degradation, and hence not suitable for video coding scenario. In this work, we propose a video pre-processing approach by leveraging edge preserving filter specifically designed for video coding, of which filter parameters are optimized in the sense of rate-distortion (R-D) performance. The proposed pre-processing method removes low R-D cost-effective components for video encoder while keeping important structural components, leading to higher coding efficiency and also better subjective quality. Comparing with the conventional denoising filters, our proposed pre-processing method using the R-D optimized edge preserving filter can improve the coding efficiency by up to -5.2% BD-rate with low computational complexity.

关键词： video coding video pre-processing rate-distortion prefilter

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Based EBCOT Source Symbol Prediction Technique for JPEG2000 image Compression Architecture

Deep Learning Based EBCOT Source Symbol Prediction Technique...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Wang, I-Hsiang Ding, Jian-Jiun Natl Taiwan Univ Grad Inst Commun Engn Taipei Taiwan

ISBN: (纸本)9781728180687

In this work, an efficient and robust learning-based JPEG2000 architecture is proposed. It uses machine learning techniques for predicting and encoding the decision bit in the embedded block coding with optimized truncation (EBCOT) process. First, we apply non-locally weighted ridge regression to predict the quantized wavelet coefficients in the LL subband. Then, during the EBCOT process, we perform inter/intra subband prediction and inter/intra bit plane symbol prediction to estimate the activity of the decision bit using the deep learning architecture. Then, the binary prediction result is treated as an additional context and the decision bit is eventually coded using an advanced context-based adaptive binary arithmetic coder. Simulations show that the proposed framework provides the same visual quality as conventional codecs with as much as 30% bitrate savings.

关键词： image compression JPEG2000 machine learning deep learning adaptive arithmetic coding

来源：评论

学校读者我要写书评

暂无评论

Dual-stream Self-attention Network for image Captioning

Dual-stream Self-attention Network for Image Captioning

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Wan, Boyang Jiang, Wenhui Fang, Yuming Wen, Wenying Liu, Hantao Jiangxi Univ Finance & Econ Nanchang Jiangxi Peoples R China Cardiff Univ Cardiff Wales

ISBN: (纸本)9781665475921

Self-attention based encoder-decoder models achieve dominant performance in image captioning. However, most existing image captioning models (ICMs) only focus on modeling the relation between spatial tokens, while channel-wise attention is neglected for getting visual representation. Considering that different channels of visual representation usually denote different visual objects, it may lead to poor performance in terms of object and attribute words in the captioning sentences generated by the ICMs. In this paper, we propose a novel dual-stream self-attention module (DSM) to alleviate the above issue. Specifically, we propose a parallel self-attention based module that simultaneously encodes visual information from the spatial and channel dimensions. Besides, to obtain channel-wise visual features effectively and efficiently, we introduce a group self-attention block with linear computational complexity. To validate the effectiveness of our model, we conduct extensive experiments on the standard IC benchmarks including MSCOCO and Flickr30k. Without bells and whistles, the proposed model performs new SOTAs containing 135.4 CIDEr score on MSCOCO and 70.8 CIDEr score on Flickr30k.

关键词： image Captioning Self-Attention Spatial Attention Channel Attention

来源：评论

学校读者我要写书评

暂无评论

Automatic image Cropping based on Bottom-up Saliency and Top-down Semantics

Automatic Image Cropping based on Bottom-up Saliency and Top...

引用

IEEE Pacific Rim conference on communications, Computers and Signal processing (PACRIM)

作者： Lin, Jiang Bajic, Ivan V. Simon Fraser Univ Sch Engn Sci Burnaby BC Canada

ISBN: (纸本)9781538607008

Automatic image cropping techniques have been developed recently to address the mismatch between the native display and image characteristics, such as resolution, aspect ratio, etc. These techniques usually rely on determining the importance of various regions in the image, or the aesthetic appeal of the final cropped image. In this work, we present a cropping method that combines bottom-up visual saliency and top-down semantic analysis to create a cropped image that best preserves important image content. Experimental results illustrate that the new method outperforms popular saliency-based cropping, which only relies on bottom-up analysis.

关键词： automatic image cropping bottom-up visual saliency top-down semantics

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共455页 << < 10 11 12 13 14 15 16 17 18 19 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：